Extractive summarization very short about transformersum

[Geethi2020]

Thank you for the quick response Housen and for the direction.

[HHousen]

Whoops! Yes, the number of top sentences to select was hardcoded to 2 in the ExtractiveSummarizer.predict() function. Yes, the top n sentences are returned. I've updated the library so the ExtractiveSummarizer.predict() function has a num_summary_sentences argument to specify the number of sentences in the output summary. The default is 3 sentences. Let me know if this works 😄.

[Geethi2020]

Hi, Is there any upper limit for num_summary_sentences ? Wanted to create a summary of 100 sentences from an article of 200+ sentences using MobileBERT. It gives only 8 sentences (or below if num_summary_sentences is smaller), regardless of num_summary_sentences value. Please advise. Thank you.

[HHousen]

Yes, there is an upper limit since the decoder of most BART-Like models can only output 512 tokens. Transformers generally cannot handle long sequences of input or output. The Longformer would be your best option since it can handle an input of about 8000/16000 (depending on the version) tokens but still only outputs 512 tokens. If you wanted a summary that long then you should use a standard algorithm like TextRank.